The research of the VLSI Information Processing (VIP) group is at the intersection of wireless communication, digital signal processing (DSP), and
very-large-scale integration (VLSI) circuit and system design.
Our main focus is on developing novel algorithms for applications demanding high throughput,
low latency, and best solution quality,
and integrating them
into efficient (in terms of power consumption, throughput, and silicon area) application-specific
integrated circuits (ASICs) and field-programmable gate arrays (FPGAs).
To arrive at best-in-class hardware designs,
we are jointly considering communication and information theory, signal processing, algorithm development, architecture design, and
hardware implementation aspects, which enables far more efficient solutions than conventional, atomistic
DSP or VLSI design approaches that solely focus on one of the two fields.
Our current research focus is on theory, algorithms, and VLSI circuits for low-precision
massive (or large-scale) multi-user multiple-input multiple-output (MU-MIMO) wireless systems,
analog-to-feature (A2F) conversion for low-power signal classification,
(non-)convex optimization for real-time signal recovery from nonlinear measurements (including phase retrieval problems),
as well as machine learning in the realms of wireless system design.
In all of these fields, we build upon recent progress in convex and non-convex optimization,
sparse signal recovery and compressive sensing,
graphical models, Bayesian inference, dimensionality reduction, and manifold learning.

News

November 5, 2018

October 29, 2018

Paper by Ph.D. students Kaipeng Li (Rice University) and Charles Jeon (Cornell University)
on "Feedforward Architectures for Decentralized Precoding in Massive MU-MIMO Systems," was
awarded 2nd place at the student paper contest of the 52nd Annual Asilomar Conference on
Signals, Systems, and Computers.

September 27, 2018

Two of our undergraduate students, Maria Bobbett and Yirong Chen, received a research award
from Cornell's Engineering Learning Initiatives (ELI). Maria will be working on parallel processing in
associative memories and Yirong on radio-frequency spectrum sensing via deep neural networks.

September 19, 2018

New collaborative NSF Grant on "SPASS: Spatio-Spectral Sensing with Wideband Feature Extraction Arrays."
Total funding is $641,999 for three years.

September 5, 2018

Two papers accepted at the 32nd Conference on Neural Information Processing Systems (NIPS); preprints will be available shortly.

August 21, 2018

Journal paper on channel charting has been accepted to IEEE Access.
ArXiv preprint available here!

August 20, 2018

The VIP group welcomes three new Ph.D. students: Alexandra Gallyas Sanhueza, Seyed Hadi Mirfarshbafan, and Said Medjkouh!

August 14, 2018

July 16, 2018

New journal paper on a novel concept we call Channel Charting, which enables passive (unsupervised) user localization in multi-antenna wireless
systems from channel-state information using dimensionality reduction and machine learning techniques. Conference version of the paper has been
accepted at the IEEE Global Communications Conference (GLOBECOM).
ArXiv preprint of the journal paper available here!

May 11, 2018

May 8, 2018

Two of our M.Eng. projects won a Cornell ECE M.Eng. best poster award.
Congratulations to
Doug Stiverson on his work "Parametric Channel Estimation for Multi-Antenna mmWave Communication," and
to Suyao Liu and Xinyu Wang on their work on "DeepViz: Machine Learning Based Visualization."

April 5, 2018

New paper on targeted clean-label poisoning attacks on neural networks.
Preprint available here!

November 28, 2017

November 25, 2017

Another one: 9th journal paper accepted this year. The paper will appear in the IEEE Transactions on Information Theory and proposes
a new convex method called PhaseMax for phase retrieval that is lifting-free and comes with
sharp, nonasymptotic recovery guarantees.
arXiv preprint available here!

November 15, 2017

One more: 8th journal paper accepted this year. The paper proposes the a decentralized architecture for baseband processing in massive MIMO systems and
will appear in the IEEE Journal on Emerging and Selected Topics in Circuits and Systems (JETCAS) special issue on "Advanced Baseband Processing
Circuits and Systems for 5G Communications";
preprint available here!

November 7, 2017

7th journal paper accepted this year! The paper proposes the first VLSI designs for nonlinear 1-bit precoding in massive
MIMO systems and will appear in the IEEE Journal on Emerging and Selected Topics in Circuits and Systems (JETCAS) special issue on "Advanced Baseband Processing
Circuits and Systems for 5G Communications";
preprint available here!

October 24, 2017

Siemens Healthineers has licensed a compressive sensing patent of Prof. Studer and collaborators from Rice University and Carnegie Mellon University
that reduces long MRI scan times while maintaining high diagnostic quality;
see the press release here!

September 22, 2017

6th journal paper accepted this year! New paper on joint data detection and channel estimation for large SIMO wireless systems to appear in the IEEE Transactions on Circuits and Systems-I: Regular Papers;
preprint here!

August 31, 2017

New preprint on quantized precoding in massive MIMO-OFDM systems on arXiv:
click here!